MEMS Graduate Student Research Assistant (RA): MS or PhD
MEMS
Position Title:
Dynamic System State Estimation and Control for Transformer and Storage Grid Analytics
Position Description:
The Department of Mechanical Engineering and Materials Science (MEMS) at the University of Pittsburgh invites applications for a Graduate Student Research Assistant (RA) at the MS or PhD level, with an emphasis on state estimation, embedded control systems, and edge hardware prototyping coupled with artificial intelligence (AI) and machine learning (ML) techniques applied to sensor systems. Initial application focuses on grid-scale Li-ion-based battery management systems and power transformer health monitoring systems. More specifically, the student will develop edge analytics techniques which estimate several existing and newly-defined internal states of the electrical asset indicating its health conditions, including both normal and faulty operational conditions. Analytics will leverage real-time data from existing and developing sensor technologies under development within the group. In interfacing with the sensors, the first stage of the development will include on-device calibration models tailored to specific sensor training datasets. Prior knowledge or experience with edge devices such as microcontroller (MCU) prototyping and programming is desirable. Techniques such as Tiny-ML engines implementation on MCUs will be explored and demonstrated to complete the sensor signal interrogation and post-processing. The candidate will have an opportunity to work closely with DOE national laboratory, industry, and other academic collaborators in development and application of the state estimation control system and edge analytics with experimental sensor data interrogation framework in part through the University of Pittsburgh Infrastructure Sensing Collaboration.
Desired Interests and Qualifications:
Successful applicants should have interest in embedded system, control algorithm, on-device analytics with AI techniques, and applications of battery and grid asset sensor technologies. Applicants should have a BS or MS degree in electrical engineering, computer engineering, robotics control or related field. Candidates with experience in embedded system, MCU/PCB prototyping, and fundamentals in computer architecture and firmware development are preferred. Prior knowledge and experience with control theory and state estimation is a plus.
Anticipated Start Date:
Summer 2024 or Fall 2024 Semester
Application Details:
Interested candidates should contact Prof. Paul Ohodnicki with an updated resume at pro8@pitt.edu and also submit an application to the electrical engineering graduate program at their soonest opportunity.